Related Experiment Video
Updated: Jan 29, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Subtype-Specific Brain Atrophy and White Matter Alterations in Mild Cognitive Impairment
Liangpeng Wei1,2,3, Jiaming Lu1,2,3, Xin Li1,2,3
1Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, No. 321 Zhongshan Road, Nanjing 210008, China.
Abstract:
Background/Objectives: Identifying pathological distinctions among mild cognitive impairment (MCI) subtypes is important for differentiating dementia. The purpose of this study is to investigate subtype-specific structural alterations in amnestic MCI (aMCI) and non-amnestic MCI (naMCI) and evaluate their potential as imaging biomarkers for subtype classification. Methods: T1 and DTI MRI data from two independent cohorts were analyzed, including a discovery dataset (58 aMCI, 35 naMCI, and 95 NC) and a replication dataset (61 aMCI, 39 naMCI, and 67 NC). Surface-based morphometry and automated fiber quantification (AFQ) were used to examine cortical thickness and white matter microstructure. Mediation models were used to explore the links between brain structure and cognitive outcomes. A logistic regression model was applied to evaluate classification performance. Results: The aMCI exhibited right hippocampal atrophy. In the naMCI, reduced cortical thickness was observed in the right anterior cingulate cortex (rACC) and opercular inferior frontal gyrus, along with increased fractional anisotropy (FA) in the right inferior fronto-occipital fasciculus (IFOF). These alterations were linked to domain-specific cognitive deficits. Moreover, partial mediation effects of IFOF FA values were observed in the link between rACC thickness and cognitive outcomes. Furthermore, these structural alterations effectively distinguished between aMCI and naMCI, showing stable performance across independent datasets (Accuracy = 0.821, AUC = 0.904). Conclusions: Our findings reveal distinct structural alterations across MCI subtypes, providing deeper insight into the heterogeneous mechanisms of dementia and supporting the potential of imaging markers for the diagnosis of MCI subtypes.
Insights
This study found distinct brain structure differences in amnestic mild cognitive impairment (aMCI) and non-amnestic mild cognitive impairment (naMCI). These imaging biomarkers can help classify MCI subtypes and differentiate dementia.
Area of Science:
- Neuroimaging
- Neurology
- Biomarkers
Background:
- Distinguishing mild cognitive impairment (MCI) subtypes is crucial for early dementia differentiation.
- Subtype-specific pathological changes in MCI remain incompletely understood.
Purpose of the Study:
- To investigate subtype-specific structural brain alterations in amnestic MCI (aMCI) and non-amnestic MCI (naMCI).
- To evaluate the potential of these alterations as imaging biomarkers for MCI subtype classification.
Main Methods:
- Analysis of T1 and diffusion tensor imaging (DTI) MRI data from two independent cohorts.
- Utilized surface-based morphometry and automated fiber quantification (AFQ) for cortical thickness and white matter analysis.
- Employed mediation models and logistic regression for evaluating brain-behavior relationships and classification performance.
Main Results:
- Amnestic MCI (aMCI) showed right hippocampal atrophy.
- Non-amnestic MCI (naMCI) exhibited reduced cortical thickness in the right anterior cingulate cortex (rACC) and opercular inferior frontal gyrus, with increased fractional anisotropy (FA) in the right inferior fronto-occipital fasciculus (IFOF).
- These structural changes correlated with cognitive deficits and accurately classified aMCI vs. naMCI (Accuracy=0.821, AUC=0.904).
Conclusions:
- Distinct structural alterations characterize aMCI and naMCI, offering insights into dementia heterogeneity.
- Identified imaging markers show promise for the diagnostic classification of MCI subtypes.
- Findings support the utility of neuroimaging in understanding and diagnosing MCI.
Related Concept Videos
Cognitive Dissonance
Physical and Chemical Properties of Matter
Classifying Matter by State
Classifying Matter by Composition
According to its composition, the matter can be classified into two broad categories — pure substances and mixtures.
A pure substance is a form of matter that has a constant composition throughout with uniform properties. For example, any sample of sucrose has the same composition and same physical properties, such as melting point, color, and sweetness, regardless of the source from which it is isolated.
A mixture is composed of two or...
The Atomic Theory of Matter
What is Matter?

